US2012317249A1PendingUtilityA1

Methods and systems for extreme capacity management

33
Individually held — no corporate assignee on recordPriority: Jun 13, 2011Filed: Jun 13, 2011Published: Dec 13, 2012
Est. expiryJun 13, 2031(~4.9 yrs left)· nominal 20-yr term from priority
Inventors:Michael A. SalsburgSteve Guarrieri
G06F 9/5072
33
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Claims

Abstract

Embodiments of the disclosed invention include an apparatus, method, and computer program product for. In one embodiment, a machine-readable tangible and non-transitory medium having instructions for managing resources is disclosed. The instructions when read by a machine, causes the machine to establish a workload profile for each tier within a plurality of tiers based on a computing request rate, a network request rate, and a storage request rate for each of the tiers. The machine also determines a configuration based on the workload profile for each of the tiers, wherein the configuration balances the computing request rate, the network request rate, and the storage request rate for each of the tiers.

Claims

exact text as granted — not AI-modified
1 . A computer implemented method for configuring a system, the method comprising:
 establishing, using a processor, a workload profile for each of a plurality tiers based on a computing request rate, a network request rate, and a storage request rate for each of the tiers; and   determining, using the processor, a configuration of the system based on the workload profile for each of the tiers, wherein the configuration balances the computing request rate, the network request rate, and the storage request rate for each of the tiers such that the computing request rate, the network request rate, and the storage request rate are configured to reach maximum utilization at approximately the same time.   
     
     
         2 . The method of  claim 1 , wherein the plurality of tiers comprises a web tier, an application tier, and data tier. 
     
     
         3 . The method of  claim 1 , wherein the systems are servers in a datacenter of a cloud service provider. 
     
     
         4 . The method of  claim 1 , wherein establishing the workload profile includes utilizing statistics gathered by an operating system. 
     
     
         5 . The method of  claim 1 , wherein determining the configuration includes selecting from a plurality of preconfigured platform optimized design components (PODs). 
     
     
         6 . The method of  claim 5 , wherein the plurality of preconfigured PODs includes a preconfigured server POD, a preconfigured network POD, and a preconfigured storage POD. 
     
     
         7 . The method of  claim 5 , wherein each of the PODs are uniquely preconfigured to match a workload profile for a particular tier. 
     
     
         8 . The method of  claim 7 , wherein the PODs are uniquely preconfigured with both hardware and software components. 
     
     
         9 . The method of  claim 1 , further comprising:
 establishing a change factor based on an estimation of a new utilization rate against a current utilization rate for upgrading the systems, the estimation based on an industry standard benchmark.   
     
     
         10 . The method of  claim 1 , wherein the established workload profile is hardware independent. 
     
     
         11 . A machine-readable tangible and non-transitory medium having instructions for managing resources, wherein the instructions, when read by the machine, causes a machine to perform the following:
 establish a workload profile for each tier within a plurality of tiers based on a computing request rate, a network request rate, and a storage request rate for each of the tiers; and   determine a configuration based on the workload profile for each of the tiers, wherein the configuration balances the computing request rate, the network request rate, and the storage request rate for each of the tiers.   
     
     
         12 . The medium of  claim 11 , wherein the plurality of tiers consists of a web tier, an application tier, and data tier. 
     
     
         13 . The medium of  claim 11 , wherein the resources are servers in a datacenter of a cloud service provider. 
     
     
         14 . The medium of  claim 11 , wherein establishing the workload profile includes utilizing statistics gathered by an operating system. 
     
     
         15 . The medium of  claim 11 , wherein determining the configuration includes selecting from a plurality of preconfigured platform optimized design components (PODs). 
     
     
         16 . The medium of  claim 15 , wherein the plurality of preconfigured PODs includes a preconfigured server POD, a preconfigured network POD, and a preconfigured storage POD. 
     
     
         17 . The medium of  claim 15 , wherein each of the PODs are uniquely preconfigured to match a workload profile for a particular tier. 
     
     
         18 . The medium of  claim 17 , wherein the PODs are uniquely preconfigured with both hardware and software components. 
     
     
         19 . The medium of  claim 11 , further comprising:
 establishing a change factor based on an estimation of a new utilization rate against a current utilization rate for upgrading the resources.   
     
     
         20 . A system comprising:
 a memory operable to store computer executable instructions;   a processor configured to execute the computer executable instructions to:
 establish a workload profile for each tier within a plurality of tiers based on a computing request rate, a network request rate, and a storage request rate for each of the tiers; and 
 determine a configuration based on the workload profile for each of the tiers, wherein the configuration balances the computing request rate, the network request rate, and the storage request rate for each of the tiers.

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